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<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="#pro-methods">Protected 成员函数</a> &#124;
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<div class="title">pcl::gpu::EuclideanLabeledClusterExtraction&lt; PointT &gt; 模板类 参考</div>  </div>
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<p><b><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html" title="EuclideanLabeledClusterExtraction represents a segmentation class for cluster extraction in an Euclid...">EuclideanLabeledClusterExtraction</a></b> represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree  
 <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="gpu__extract__labeled__clusters_8h_source.html">gpu_extract_labeled_clusters.h</a>&gt;</code></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:a139efa65a70cb6f1efcfa17ad81306f4"><td class="memItemLeft" align="right" valign="top"><a id="a139efa65a70cb6f1efcfa17ad81306f4"></a>
typedef <a class="el" href="structpcl_1_1_point_x_y_z.html">pcl::PointXYZ</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointType</b></td></tr>
<tr class="separator:a139efa65a70cb6f1efcfa17ad81306f4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8cb2814670f57a57a79ac771884487c7"><td class="memItemLeft" align="right" valign="top"><a id="a8cb2814670f57a57a79ac771884487c7"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHost</b></td></tr>
<tr class="separator:a8cb2814670f57a57a79ac771884487c7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b64330bd728040602ec04175d401fc4"><td class="memItemLeft" align="right" valign="top"><a id="a6b64330bd728040602ec04175d401fc4"></a>
typedef PointCloudHost::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHostPtr</b></td></tr>
<tr class="separator:a6b64330bd728040602ec04175d401fc4"><td class="memSeparator" colspan="2">&#160;</td></tr>
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typedef PointCloudHost::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudHostConstPtr</b></td></tr>
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typedef PointIndices::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesPtr</b></td></tr>
<tr class="separator:a3d6145c5b6fbab6b7de6755d17ee7d7d"><td class="memSeparator" colspan="2">&#160;</td></tr>
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typedef PointIndices::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointIndicesConstPtr</b></td></tr>
<tr class="separator:a1710e55020ef7b4560d28a4c84633383"><td class="memSeparator" colspan="2">&#160;</td></tr>
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typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html">pcl::gpu::Octree</a>&#160;</td><td class="memItemRight" valign="bottom"><b>GPUTree</b></td></tr>
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typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html#aaef633c03e07b4ccf653afa6f314be75">pcl::gpu::Octree::Ptr</a>&#160;</td><td class="memItemRight" valign="bottom"><b>GPUTreePtr</b></td></tr>
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<tr class="memitem:a2b523a979960c350186ca017f3ecc9ad"><td class="memItemLeft" align="right" valign="top"><a id="a2b523a979960c350186ca017f3ecc9ad"></a>
typedef <a class="el" href="classpcl_1_1gpu_1_1_octree.html#a2584f9e71b717c8c891415199661a2c3">pcl::gpu::Octree::PointCloud</a>&#160;</td><td class="memItemRight" valign="bottom"><b>CloudDevice</b></td></tr>
<tr class="separator:a2b523a979960c350186ca017f3ecc9ad"><td class="memSeparator" colspan="2">&#160;</td></tr>
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Public 成员函数</h2></td></tr>
<tr class="memitem:a2c8faf599e9aca053eb022fea0b18ebc"><td class="memItemLeft" align="right" valign="top"><a id="a2c8faf599e9aca053eb022fea0b18ebc"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a2c8faf599e9aca053eb022fea0b18ebc">EuclideanLabeledClusterExtraction</a> ()</td></tr>
<tr class="memdesc:a2c8faf599e9aca053eb022fea0b18ebc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor. <br /></td></tr>
<tr class="separator:a2c8faf599e9aca053eb022fea0b18ebc"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a715b207187d87dc7ab28dcea035eb7f6"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a715b207187d87dc7ab28dcea035eb7f6">setSearchMethod</a> (const GPUTreePtr &amp;tree)</td></tr>
<tr class="memdesc:a715b207187d87dc7ab28dcea035eb7f6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the search object.  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a715b207187d87dc7ab28dcea035eb7f6">更多...</a><br /></td></tr>
<tr class="separator:a715b207187d87dc7ab28dcea035eb7f6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4639debabce4242c7dd0c9884ab1ac7a"><td class="memItemLeft" align="right" valign="top">GPUTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a4639debabce4242c7dd0c9884ab1ac7a">getSearchMethod</a> ()</td></tr>
<tr class="memdesc:a4639debabce4242c7dd0c9884ab1ac7a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the search method used.  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a4639debabce4242c7dd0c9884ab1ac7a">更多...</a><br /></td></tr>
<tr class="separator:a4639debabce4242c7dd0c9884ab1ac7a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a02c83d15475d500a42f632762fac8c99"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a02c83d15475d500a42f632762fac8c99">setClusterTolerance</a> (double tolerance)</td></tr>
<tr class="memdesc:a02c83d15475d500a42f632762fac8c99"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the spatial cluster tolerance as a measure in the L2 Euclidean space  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a02c83d15475d500a42f632762fac8c99">更多...</a><br /></td></tr>
<tr class="separator:a02c83d15475d500a42f632762fac8c99"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae11c90e1dc47324cf2db5daca5c8f298"><td class="memItemLeft" align="right" valign="top"><a id="ae11c90e1dc47324cf2db5daca5c8f298"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ae11c90e1dc47324cf2db5daca5c8f298">getClusterTolerance</a> ()</td></tr>
<tr class="memdesc:ae11c90e1dc47324cf2db5daca5c8f298"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the spatial cluster tolerance as a measure in the L2 Euclidean space. <br /></td></tr>
<tr class="separator:ae11c90e1dc47324cf2db5daca5c8f298"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af78965e6beeb6d58964f24db03eed74c"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#af78965e6beeb6d58964f24db03eed74c">setMinClusterSize</a> (int min_cluster_size)</td></tr>
<tr class="memdesc:af78965e6beeb6d58964f24db03eed74c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the minimum number of points that a cluster needs to contain in order to be considered valid.  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#af78965e6beeb6d58964f24db03eed74c">更多...</a><br /></td></tr>
<tr class="separator:af78965e6beeb6d58964f24db03eed74c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a790f792da7631a782854b2dc30e58418"><td class="memItemLeft" align="right" valign="top"><a id="a790f792da7631a782854b2dc30e58418"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a790f792da7631a782854b2dc30e58418">getMinClusterSize</a> ()</td></tr>
<tr class="memdesc:a790f792da7631a782854b2dc30e58418"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the minimum number of points that a cluster needs to contain in order to be considered valid. <br /></td></tr>
<tr class="separator:a790f792da7631a782854b2dc30e58418"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9e2c2fd2acdb4ff0dfe9e03fd9ee2169"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a9e2c2fd2acdb4ff0dfe9e03fd9ee2169">setMaxClusterSize</a> (int max_cluster_size)</td></tr>
<tr class="memdesc:a9e2c2fd2acdb4ff0dfe9e03fd9ee2169"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the maximum number of points that a cluster needs to contain in order to be considered valid.  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a9e2c2fd2acdb4ff0dfe9e03fd9ee2169">更多...</a><br /></td></tr>
<tr class="separator:a9e2c2fd2acdb4ff0dfe9e03fd9ee2169"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab157463c67beea6c3611b0b84955ae99"><td class="memItemLeft" align="right" valign="top"><a id="ab157463c67beea6c3611b0b84955ae99"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ab157463c67beea6c3611b0b84955ae99">getMaxClusterSize</a> ()</td></tr>
<tr class="memdesc:ab157463c67beea6c3611b0b84955ae99"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the maximum number of points that a cluster needs to contain in order to be considered valid. <br /></td></tr>
<tr class="separator:ab157463c67beea6c3611b0b84955ae99"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9028eef930d62363d0ff7c2ea9657d7d"><td class="memItemLeft" align="right" valign="top"><a id="a9028eef930d62363d0ff7c2ea9657d7d"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><b>setInput</b> (<a class="el" href="classpcl_1_1gpu_1_1_device_array.html">CloudDevice</a> input)</td></tr>
<tr class="separator:a9028eef930d62363d0ff7c2ea9657d7d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6f7f93a4394c75b7b1be9e68645b3892"><td class="memItemLeft" align="right" valign="top"><a id="a6f7f93a4394c75b7b1be9e68645b3892"></a>
void&#160;</td><td class="memItemRight" valign="bottom"><b>setHostCloud</b> (PointCloudHostPtr host_cloud)</td></tr>
<tr class="separator:a6f7f93a4394c75b7b1be9e68645b3892"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a55f5da27101dc036466ad8479a719524"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a55f5da27101dc036466ad8479a719524">extract</a> (std::vector&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &gt; &amp;clusters)</td></tr>
<tr class="memdesc:a55f5da27101dc036466ad8479a719524"><td class="mdescLeft">&#160;</td><td class="mdescRight">Cluster extraction in a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> given by &lt;setInputCloud (), setIndices ()&gt;  <a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a55f5da27101dc036466ad8479a719524">更多...</a><br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected 成员函数</h2></td></tr>
<tr class="memitem:a3c34f90db5371691257773eeff43005d"><td class="memItemLeft" align="right" valign="top"><a id="a3c34f90db5371691257773eeff43005d"></a>
virtual std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a3c34f90db5371691257773eeff43005d">getClassName</a> () const</td></tr>
<tr class="memdesc:a3c34f90db5371691257773eeff43005d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Class getName method. <br /></td></tr>
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</table><table class="memberdecls">
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Protected 属性</h2></td></tr>
<tr class="memitem:a014abaa2a0d27877b92c21ef8ab54a01"><td class="memItemLeft" align="right" valign="top"><a id="a014abaa2a0d27877b92c21ef8ab54a01"></a>
<a class="el" href="classpcl_1_1gpu_1_1_device_array.html">CloudDevice</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a014abaa2a0d27877b92c21ef8ab54a01">input_</a></td></tr>
<tr class="memdesc:a014abaa2a0d27877b92c21ef8ab54a01"><td class="mdescLeft">&#160;</td><td class="mdescRight">the input cloud on the GPU <br /></td></tr>
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PointCloudHostPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8bfe9c8bc45fc969836e8847a219a136">host_cloud_</a></td></tr>
<tr class="memdesc:a8bfe9c8bc45fc969836e8847a219a136"><td class="mdescLeft">&#160;</td><td class="mdescRight">the original cloud the Host <br /></td></tr>
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<tr class="memitem:a150cd35b31a3e3b17394186a5d72b9e0"><td class="memItemLeft" align="right" valign="top"><a id="a150cd35b31a3e3b17394186a5d72b9e0"></a>
GPUTreePtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a></td></tr>
<tr class="memdesc:a150cd35b31a3e3b17394186a5d72b9e0"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the spatial search object. <br /></td></tr>
<tr class="separator:a150cd35b31a3e3b17394186a5d72b9e0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8585a773e7074e619ecbf2db888e85d5"><td class="memItemLeft" align="right" valign="top"><a id="a8585a773e7074e619ecbf2db888e85d5"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8585a773e7074e619ecbf2db888e85d5">cluster_tolerance_</a></td></tr>
<tr class="memdesc:a8585a773e7074e619ecbf2db888e85d5"><td class="mdescLeft">&#160;</td><td class="mdescRight">The spatial cluster tolerance as a measure in the L2 Euclidean space. <br /></td></tr>
<tr class="separator:a8585a773e7074e619ecbf2db888e85d5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a42829d268fb7b383386ae9d77e5bee6f"><td class="memItemLeft" align="right" valign="top"><a id="a42829d268fb7b383386ae9d77e5bee6f"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a42829d268fb7b383386ae9d77e5bee6f">min_pts_per_cluster_</a></td></tr>
<tr class="memdesc:a42829d268fb7b383386ae9d77e5bee6f"><td class="mdescLeft">&#160;</td><td class="mdescRight">The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). <br /></td></tr>
<tr class="separator:a42829d268fb7b383386ae9d77e5bee6f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae4ee5100c3a35b894a9154af84dfb2df"><td class="memItemLeft" align="right" valign="top"><a id="ae4ee5100c3a35b894a9154af84dfb2df"></a>
int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ae4ee5100c3a35b894a9154af84dfb2df">max_pts_per_cluster_</a></td></tr>
<tr class="memdesc:ae4ee5100c3a35b894a9154af84dfb2df"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). <br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointT&gt;<br />
class pcl::gpu::EuclideanLabeledClusterExtraction&lt; PointT &gt;</h3>

<p><b><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html" title="EuclideanLabeledClusterExtraction represents a segmentation class for cluster extraction in an Euclid...">EuclideanLabeledClusterExtraction</a></b> represents a segmentation class for cluster extraction in an Euclidean sense, depending on pcl::gpu::octree </p>
<dl class="section author"><dt>作者</dt><dd>Koen Buys, Radu Bogdan Rusu </dd></dl>
</div><h2 class="groupheader">成员函数说明</h2>
<a id="a55f5da27101dc036466ad8479a719524"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a55f5da27101dc036466ad8479a719524">&#9670;&nbsp;</a></span>extract()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::extract </td>
          <td>(</td>
          <td class="paramtype">std::vector&lt; <a class="el" href="structpcl_1_1_point_indices.html">PointIndices</a> &gt; &amp;&#160;</td>
          <td class="paramname"><em>clusters</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Cluster extraction in a <a class="el" href="classpcl_1_1_point_cloud.html" title="PointCloud represents the base class in PCL for storing collections of 3D points.">PointCloud</a> given by &lt;setInputCloud (), setIndices ()&gt; </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">clusters</td><td>the resultant point clusters </td></tr>
  </table>
  </dd>
</dl>
<dl class="todo"><dt><b><a class="el" href="todo.html#_todo000026">待办事项:</a></b></dt><dd>what do we do if input isn't a <a class="el" href="structpcl_1_1_point_x_y_z.html" title="A point structure representing Euclidean xyz coordinates. (SSE friendly)">PointXYZ</a> cloud? </dd></dl>
<div class="fragment"><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;{</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;  <span class="comment">// Initialize the GPU search tree</span></div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>)</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;  {</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>.reset (<span class="keyword">new</span> <a class="code" href="classpcl_1_1gpu_1_1_octree.html">pcl::gpu::Octree</a>());</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>-&gt;setCloud(<a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a014abaa2a0d27877b92c21ef8ab54a01">input_</a>);</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  }</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>-&gt;isBuilt())</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  {</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>-&gt;build();</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  }</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;<span class="comment">  if(tree_-&gt;cloud_.size() != host_cloud.points.size ())</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;<span class="comment">  {</span></div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;<span class="comment">    PCL_ERROR(&quot;[pcl::gpu::EuclideanClusterExtraction] size of host cloud and device cloud don&#39;t match!\n&quot;);</span></div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;<span class="comment">    return;</span></div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;<span class="comment">  }</span></div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;<span class="comment">*/</span></div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;  <span class="comment">// Extract the actual clusters</span></div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  extractLabeledEuclideanClusters (<a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8bfe9c8bc45fc969836e8847a219a136">host_cloud_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8585a773e7074e619ecbf2db888e85d5">cluster_tolerance_</a>, clusters, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a42829d268fb7b383386ae9d77e5bee6f">min_pts_per_cluster_</a>, <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ae4ee5100c3a35b894a9154af84dfb2df">max_pts_per_cluster_</a>);</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  <span class="comment">// Sort the clusters based on their size (largest one first)</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  std::sort (clusters.rbegin (), clusters.rend (), compareLabeledPointClusters);</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_a014abaa2a0d27877b92c21ef8ab54a01"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a014abaa2a0d27877b92c21ef8ab54a01">pcl::gpu::EuclideanLabeledClusterExtraction::input_</a></div><div class="ttdeci">CloudDevice input_</div><div class="ttdoc">the input cloud on the GPU</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:133</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_a150cd35b31a3e3b17394186a5d72b9e0"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">pcl::gpu::EuclideanLabeledClusterExtraction::tree_</a></div><div class="ttdeci">GPUTreePtr tree_</div><div class="ttdoc">A pointer to the spatial search object.</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:139</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_a42829d268fb7b383386ae9d77e5bee6f"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a42829d268fb7b383386ae9d77e5bee6f">pcl::gpu::EuclideanLabeledClusterExtraction::min_pts_per_cluster_</a></div><div class="ttdeci">int min_pts_per_cluster_</div><div class="ttdoc">The minimum number of points that a cluster needs to contain in order to be considered valid (default...</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:145</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_a8585a773e7074e619ecbf2db888e85d5"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8585a773e7074e619ecbf2db888e85d5">pcl::gpu::EuclideanLabeledClusterExtraction::cluster_tolerance_</a></div><div class="ttdeci">double cluster_tolerance_</div><div class="ttdoc">The spatial cluster tolerance as a measure in the L2 Euclidean space.</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:142</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_a8bfe9c8bc45fc969836e8847a219a136"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8bfe9c8bc45fc969836e8847a219a136">pcl::gpu::EuclideanLabeledClusterExtraction::host_cloud_</a></div><div class="ttdeci">PointCloudHostPtr host_cloud_</div><div class="ttdoc">the original cloud the Host</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:136</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction_html_ae4ee5100c3a35b894a9154af84dfb2df"><div class="ttname"><a href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ae4ee5100c3a35b894a9154af84dfb2df">pcl::gpu::EuclideanLabeledClusterExtraction::max_pts_per_cluster_</a></div><div class="ttdeci">int max_pts_per_cluster_</div><div class="ttdoc">The maximum number of points that a cluster needs to contain in order to be considered valid (default...</div><div class="ttdef"><b>Definition:</b> gpu_extract_labeled_clusters.h:148</div></div>
<div class="ttc" id="aclasspcl_1_1gpu_1_1_octree_html"><div class="ttname"><a href="classpcl_1_1gpu_1_1_octree.html">pcl::gpu::Octree</a></div><div class="ttdoc">Octree implementation on GPU. It suppors parallel building and paralel batch search as well .</div><div class="ttdef"><b>Definition:</b> octree.hpp:57</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a4639debabce4242c7dd0c9884ab1ac7a">&#9670;&nbsp;</a></span>getSearchMethod()</h2>

<div class="memitem">
<div class="memproto">
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template&lt;typename PointT &gt; </div>
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          <td class="memname">GPUTreePtr <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::getSearchMethod </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
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<p>Get a pointer to the search method used. </p>
<dl class="todo"><dt><b><a class="el" href="todo.html#_todo000023">待办事项:</a></b></dt><dd>fix this for a generic search tree </dd></dl>
<div class="fragment"><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;{ <span class="keywordflow">return</span> (<a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a>); }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a02c83d15475d500a42f632762fac8c99">&#9670;&nbsp;</a></span>setClusterTolerance()</h2>

<div class="memitem">
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template&lt;typename PointT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setClusterTolerance </td>
          <td>(</td>
          <td class="paramtype">double&#160;</td>
          <td class="paramname"><em>tolerance</em></td><td>)</td>
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<p>Set the spatial cluster tolerance as a measure in the L2 Euclidean space </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">tolerance</td><td>the spatial cluster tolerance as a measure in the L2 Euclidean space </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a8585a773e7074e619ecbf2db888e85d5">cluster_tolerance_</a> = tolerance; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a9e2c2fd2acdb4ff0dfe9e03fd9ee2169">&#9670;&nbsp;</a></span>setMaxClusterSize()</h2>

<div class="memitem">
<div class="memproto">
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template&lt;typename PointT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setMaxClusterSize </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>max_cluster_size</em></td><td>)</td>
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<p>Set the maximum number of points that a cluster needs to contain in order to be considered valid. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">max_cluster_size</td><td>the maximum cluster size </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#ae4ee5100c3a35b894a9154af84dfb2df">max_pts_per_cluster_</a> = max_cluster_size; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#af78965e6beeb6d58964f24db03eed74c">&#9670;&nbsp;</a></span>setMinClusterSize()</h2>

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<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setMinClusterSize </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>min_cluster_size</em></td><td>)</td>
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<p>Set the minimum number of points that a cluster needs to contain in order to be considered valid. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">min_cluster_size</td><td>the minimum cluster size </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a42829d268fb7b383386ae9d77e5bee6f">min_pts_per_cluster_</a> = min_cluster_size; }</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a715b207187d87dc7ab28dcea035eb7f6">&#9670;&nbsp;</a></span>setSearchMethod()</h2>

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<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT &gt; </div>
<table class="mlabels">
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          <td class="memname">void <a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">pcl::gpu::EuclideanLabeledClusterExtraction</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::setSearchMethod </td>
          <td>(</td>
          <td class="paramtype">const GPUTreePtr &amp;&#160;</td>
          <td class="paramname"><em>tree</em></td><td>)</td>
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<p>Provide a pointer to the search object. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramname">tree</td><td>a pointer to the spatial search object. </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;{ <a class="code" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html#a150cd35b31a3e3b17394186a5d72b9e0">tree_</a> = tree; }</div>
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<hr/>该类的文档由以下文件生成:<ul>
<li>gpu/segmentation/include/pcl/gpu/segmentation/<a class="el" href="gpu__extract__labeled__clusters_8h_source.html">gpu_extract_labeled_clusters.h</a></li>
<li>gpu/segmentation/include/pcl/gpu/segmentation/impl/<a class="el" href="gpu__extract__labeled__clusters_8hpp_source.html">gpu_extract_labeled_clusters.hpp</a></li>
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    <li class="navelem"><b>pcl</b></li><li class="navelem"><b>gpu</b></li><li class="navelem"><a class="el" href="classpcl_1_1gpu_1_1_euclidean_labeled_cluster_extraction.html">EuclideanLabeledClusterExtraction</a></li>
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